Mining factors affecting taxi drivers’ incomes using GPS trajectories

Taxis provide essential transport services in urban areas. In the taxi industry, the income level remains a cause of concern for taxi drivers as well as regulators. Mining underlying factors affecting the income level will not only benefit the newcomers and low-income drivers but also assist in developing effective optimization algorithms for taxi operations. This paper intends to disclose the factors affecting incomes along with their quantitative influence by mining over 167 million global positioning system (GPS) records from nearly 8000 taxis in Shanghai. The authors first identify a marked difference in drivers’ incomes and categorize drivers into three income levels accordingly. The authors next investigate the overall search-delivery process, thereby defining several factors that may affect the income level. The authors then develop a generalized multi-level ordered logit (GMOL) model to find the significant factors that influence incomes. Finally, the authors compute the elasticity for those significant factors and present their contributions, as well as challenge some preconceived ideas regarding how to earn high incomes.

• Record URL:
  https://doi.org/10.1016/j.trc.2017.03.013
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X17300979
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Qin, Guoyang
  • Li, Tienan
  • Yu, Bin
  • Wang, Yunpeng
  • Huang, Zhenhua
  • Sun, Jian
• Publication Date: 2017-6

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 103-118
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 79
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Data mining; Elasticity (Economics); Global Positioning System; Income; Logits; Taxicab drivers
• Subject Areas: Data and Information Technology; Economics; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01635488
• Record Type: Publication
• Files: TRIS
• Created Date: May 25 2017 1:56PM